1. Field of the Invention
The present invention relates in general to a method for overflow testing of a blind equalizer. In particular, the present invention relates to a method to perform an overflow test of a blind equalizer without adding additional circuits.
2. Description of the Related Art
Proper detection of a signal is hampered by various sources of signal degradation. One such source is intersymbol interference where consecutive transmitted symbols interfere with each other. Other sources of signal degradation include the transmission media (i.e. wire) and analog filters. These factors produce large amplitude and group delay distortion in the signal that needs compensation.
To compensate for intersymbol interference (ISI) and other sources of signal degradation and distortion, best performance is achieved by implementing an equalizer as an adaptive filter. An adaptive filter can modify from time instant to time instant, the coefficients, also referred to as tap weights, used in the filter to remove ISI and to compensate for amplitude and group delay distortions. The update of the tap weights is done to minimize the error at the output of the filter. This error is effectively a measure of the difference between the actual output of the filter and the expected output. The adaptive process continues until the error is at a minimum (i.e. the filter converges).
The convergence of an equalizer depends on many factors including initial tap weights, desired convergence rate, signal to noise ratio (SNR) at the input and phase changes caused by a clock recovery circuit at the receiver, and can be accomplished with various adaptive algorithms.
The adaptation of the tap weights in adaptive equalizers is based on an assumed correct decision about which symbol was received. This assumption is valid for equalizers with a training sequence for which the received symbol is in fact known in advance. Equalizers, however, are also used without the benefit of a training sequence, in which case the decision is not necessarily correct. These equalizers are referred to as blind equalizers. The term blind refers to trying to find the correct equalizer coefficients without a reference training sequence, therefore during convergence the decisions may be incorrect and the coefficients (weights) erroneously updated. Although the possibility of a mistake exists, if the blind equalizer makes correct decisions for a sufficiently large set of received symbols, the equalizer will converge correctly.
FIG. 1 is a block diagram illustrating a blind equalizer in the prior art. A blind equalizer 100 is a transversal finite impulse response filter (FIR). A set of continuous information X1(n), X2(n), . . . , XM(n) input to the blind equalizer 100. The set of continuous information convolute a set of tap weights W1, W2, . . . , WM in the blind equalizer 100 to produce an output of the blind equalizer rI(n).
The blind equalizer 100 adapts the tap weights to compensate for intersymbol interference (ISI) and other sources of signal degradation and distortion. The output of the blind equalizer rI(n) inputs to a slicer 102. Then, the slicer produces an output of the slicer rO(n). An error e(n) defines a measure of the difference between the output of the slicer rO(n) and the output of the blind equalizer rI(n). Thus, e(n)=rO(n)xe2x88x92rI(n). Then, the error e(n) is fed back to the blind equalizer 100 to adapt the tap weights.
The blind equalizer, as shown in FIG. 1, uses the output of the slicer rO(n) as a training sequence d(n). After completing the adaptation, the output of the blind equalizer rI(n) almost equals to the training sequence d(n). In other equalizers, the training sequence d(n) is provided from the outside device, not from the output of the slicer rO(n). Therefore, after inputting a training sequence with high power from the outside device, the output of the equalize will rapidly increase and tap weights will overflow. On the contrary, for a blind equalizer, because the training sequence d(n) is provided from the output of the slicer rO(n), it is impossible to provide a training sequence with high power to make the blind equalizer overflow. Therefore, in order to perform overflow test of a blind equalizer, additional circuits must be added. It is not economical to add additional circuits to perform an overflow test of a blind equalizer. In addition, in the prior art, a special tap weight to perform an overflow test can be designed.
An object of the present invention is to provide a method to perform an overflow test of a blind equalizer without adding additional circuits and to designate special tap weights of the blind equalizer to overflow.
Another object of the present invention is to make it possible to designate special tap weights of the blind equalizer to overflow.
To realize the above objects, the invention provides a method for overflow testing of a blind equalizer where a blind equalizer adapts an input signal by adjusting a plurality of tap weights in the blind equalizer. The method comprises the following steps: providing a primary located signal in a primary signaling point of a period by a signal generating loop; multiplying the primary located signal by a set of continuously decreasing signals to get a primary signal; providing an interfering located signal in a plurality of interfering signaling points of the period by a ISI generating loop, wherein the interfering signaling points are different from the primary signaling point; multiplying the interfering located signal by a set of continuous signals to get an interference signal; adding the primary signal and the interference signal to get the input signal; and inputting the input signal to the blind equalizer to adapt the input signal, wherein the tap weights corresponding to the interference signal in the blind equalizer overflow. An initial status of the ISI generating loop is determined by a slicing level of a slicer, amplitudes of the primary signal after the blind equalizer are larger than the slicing level and amplitudes of the interference signal after the bind equalizer are smaller than the slicing level. The primary signaling point and the interfering signaling points are chosen to decide the tap weights, which will overflow in the blind equalizer.
Furthermore, a slope formed by amplitudes of the interference signals is an interfering slope. The blind equalizer further comprises a learning constant which is bigger than the modulus of the interfering slope. A slope formed by the amplitudes of the primary signal is a primary slope. The absolute value of modulus of the primary slope is smaller than the learning constant. The blind equalizr further comprises a plurality of registers and the interval between two signals of the continuous signals and the continuously decreasing signals are bigger than the number of the registers.